Python Pandas DataFrame output as Dictionary & using MySQL sample table as source using to_dict()

We can create Python dictionary by using data from Pandas DataFrame. We will first create one Pandas DataFrame by using some sample data.

import pandas as pd
df=pd.DataFrame(data={'id': [1, 2, 3],
'name': ['John Deo', 'Max Ruin', 'Arnold'],
'class': ['Four', 'Three', 'Three'],
'mark': [75, 85, 55],
'gender': ['female', 'male', 'male']})
print(my_dict)

After creating the DataFrame we used to_dict() to create one dictionary
We can add different options to orientation while generating the dictionary. This option orient can take values like list, dict( default ) , series, split, record , index.

From MySQL database using read_sql()
We can connect to MySQL database by using SQLAlchemy engine and after connection we will create our DataFrame by using data from sample table by using read_sql.
from sqlalchemy import create_engine
sql="SELECT * FROM student LIMIT 0,10"
Here 10 rows of data from the student table is taken and displayed as dictionary .
Excel or CSV file to string
From excel file we can create string by first creating the dataframe by reading the excel file by using the method read_excel()

Similarly we can read csv file and generate JSON string

#pandas_to_dict #dataframetodict #pandasdict #plus2net #pandas #datascience #pandastutorials

[hayathbasha]

Hi facing below issue

df["Amount"] = ""
simplify.py:79: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer, col_indexer] = value instead



Can u please help me to understand this or if you create a video on this will be much helpful?